1ENG Science, techonology and material transformation processes

2024

1. A meta-learning strategy based on deep ensemble learning for tool condition monitoring of machining processes

   Procedia CIRP

2. An Autoencoder-Based Approach for Anomaly Detection of Machining Processes Using Acoustic Emission Signals

   Communications in Computer and Information Science

3. Analytical model to identify crack initiation in machined aluminium parts

   Procedia CIRP

4. Combining experimental and FEM approaches to determine the influence of workpiece temperature on fundamental variables in the machining process

   Materials Research Proceedings

5. Effect of Cutting Conditions on Surface Integrity when Robotic Drilling of Aluminum 6082-GFRP Stacks

   Procedia CIRP

6. Experimental evaluation of the maximal force before debonding a part from the build platform of an AM printer

   Materials Research Proceedings

7. Necking detection in stretch-bent materials exhibiting the Portevin-Le Chatelier effect

   Materials Research Proceedings

8. Numerical simulation of milling operations on flexible composite parts

   Materials Research Proceedings

9. OptiTwin: Data-Driven Machining Process Optimization Platform for SMEs

   IEEE International Conference on Emerging Technologies and Factory Automation, ETFA

10. Process Time Optimization of a Hot Stamping Line for Aluminum Automotive Components

    9th International Conference on Hot Sheet Metal Forming of High-Performance Steel, CHS2 2024 - Proceedings

11. Tool Geometry Optimisation for LCO2 Assisted Milling of Ti6Al4V

    Procedia CIRP

12. Tool surface texturing by shot peening: initial results and lessons learned

    IOP Conference Series: Materials Science and Engineering

13. Tool wear for finishing milling of green thermoplastic-ceramic composites fabricated with pellet AM

    Procedia CIRP